The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventor, to the extent it is described in this background section, as well as aspects of the description that may not otherwise qualify as prior art at the time of filing, are neither expressly nor impliedly admitted as prior art against the present disclosure.
Physicians and healthcare professionals rely on electrical signal data from patients to assess various types of activities. Electrocardiogram (ECG or EKG) data records electrical activity of the heart. Electroencephalography (EEG) data records electrical activity of the brain, measured along the scalp. Electromyography (EMG) data records electrical activity of skeletal muscles. The techniques for displaying such electrical signal data are uniform, but fairly old. The signal data is plotted in time measured fashion, with electrical activity on one axis and time on the other. Physicians and healthcare professionals trained in analyzing the data can analyze and diagnose some physical conditions of a patient, but to do so they often must examine long reams of data and even then some diagnostic indicators can go undetected. This is especially true for indicators of physiologic states that are either (i) long-term indicators (i.e., they develop over long periods of signal measurement) or (ii) subtle indicators, which are often masked by the data and may appear as noise or a signal anomaly.
There is a need for a better, more effective way of analyzing and displaying electrical signal data.